The present invention, is addressed to a system and a method for an improved vehicle-monitoring system in order to provide a cost-effective and scalable system design for industrial application. Machine learning and data mining technologies are used on data acquired from a plurality of vehicles in order to create models. Frequent acquisition of vehicle sensor and diagnostic data enables comparison with the created models to provide continuing analysis of the vehicle for repair, maintenance and diagnostics.
State of the art vehicles include a variety of communication systems, control systems and safety and diagnostic systems along with their associated sensors. Examples of these systems include engine control systems, diagnostic and maintenance computers, brake and stability systems and telematics devices. Exchange of information including control, status and diagnostic messages between Embedded Control Units sensors and associated devices is accomplished with a vehicle data bus infrastructure. An example is an engine bus system such as the Controller Area Network (CAN).
The on-board diagnostic systems process sensor readings and diagnostic information of the vehicle Embedded Control System in order to detect defaults. The maintenance systems on-board the vehicle continuously process sensor readings to determine the condition of the vehicle systems, parts and lubricants (e.g., brake pad wear, battery quality, and oil quality). Off-board diagnostic systems, such as workplace testing equipment, acquire vehicle diagnostics and sensor data or control on-board diagnostics and testing functions. The system uses OEM proprietary or standardized interfaces, for example, OBD to connect to the vehicle. Physical connections link the vehicle and the workshop test equipment, with short-range wireless communication systems eventually replacing cable connections. The current state of the art with respect to tele-diagnostics provides communication features of telemetrics in order to connect vehicle diagnostics systems with off-board service centers. The vehicle sends diagnostic information in the event of a breakdown and fleet operators are then able to acquire diagnostic data for maintenance and diagnostic application.
With all of these prior art systems expert knowledge based on workshop technicians"" experience or engineering knowledge for the physical or mathematical fault and maintenance models are necessary to utilize the systems diagnostics algorithms.
An object of the present invention is to provide a condition monitoring of the vehicle as an integral part of the vehicle diagnostics, maintenance and repair process. As a result of the present invention, a cost-effective and scalable system is designed which provides an industrial application whereby the use of machine learning and data mining technologies on data acquired from many vehicles provides a variety of new maintenance and diagnostics applications.
It is another object of the present invention to provide for frequent acquisition of vehicle sensor and diagnostics data and also frequent off-board analysis in order to provide for up-dated repair, maintenance and diagnostics.
The present invention provides an industrial application system infrastructure that allows for cost-effective acquisition and analysis of vehicle data for passenger cars and commercial vehicles. The present invention achieves its object by providing data analysis and knowledge generation in an approach wherein the system may use internet service applications as well as enable a new maintenance service process.